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%0 Conference Proceedings
%T VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding
%A Xu, Hu
%A Ghosh, Gargi
%A Huang, Po-Yao
%A Arora, Prahal
%A Aminzadeh, Masoumeh
%A Feichtenhofer, Christoph
%A Metze, Florian
%A Zettlemoyer, Luke
%Y Zong, Chengqing
%Y Xia, Fei
%Y Li, Wenjie
%Y Navigli, Roberto
%S Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F xu-etal-2021-vlm
%R 10.18653/v1/2021.findings-acl.370
%U https://aclanthology.org/2021.findings-acl.370
%U https://doi.org/10.18653/v1/2021.findings-acl.370
%P 4227-4239

Markdown (Informal)

[VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding](https://aclanthology.org/2021.findings-acl.370) (Xu et al., Findings 2021)

• VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding (Xu et al., Findings 2021)

ACL

• Hu Xu, Gargi Ghosh, Po-Yao Huang, Prahal Arora, Masoumeh Aminzadeh, Christoph Feichtenhofer, Florian Metze, and Luke Zettlemoyer. 2021. VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 4227–4239, Online. Association for Computational Linguistics.